Geospatial Systems - Lilian Akanazu
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Profile
Lilian Akanazu
Nottingham Geospatial Institute, University of Nottingham, NG7 2TU
Biography
About Lilian
Hi, I’m Lilian, thanks for stopping by.
I’m currently blending my passion for geohazards into an academic journey. It all began at the University of Nigeria where I obtained my Bachelors in Geography with a First class honours in 2017. However, I took detour from academics for some professional hands-on experience between 2017-2021 but like a well-researched paper, I always knew I’d be back for revisions. During my time away from academia, I worked with NEWMAP, Zenith Bank Plc, and Ernst and Young, where I acquired professional experience in environmental remediation, asset management, and financial auditing. One of my significant accomplishments was my tenure as a board member of the Accelerating Environmental Sustainability (AES) Team at EY Africa, where I represented Nigeria and supervised initiatives across 10 other African countries, earning two badges in Transformative Leadership (cross-cultural collaboration) and Climate Change.
My journey back to academia began in 2021 when I was awarded multiple fully funded scholarships, to pursue my master’s degree. Among these were the prestigious DAAD scholarship and the Glasgow Leadership Excellence Award (both of which I declined), in addition to the Erasmus Mundus scholarship and other honours. In 2023, I obtained a joint-master’s degree in Geoinformatics for Urbanised Society from the University of Tartu, Estonia; and Geoinformation Science and Earth Observation from the Université Catholique de Louvain, Belgium (avec Distinction.)
Currently, I’m interested in geohazards and disaster resilience and my research within the CDT is focused on automatically mapping landslides using satellite imagery.
Research
During my PhD, I will be focused on mapping landslides using earth observation data, which will be conducted in two phases. The first phase, completed during my MRes, involved comparing existing landslide mapping techniques to evaluate their efficiency and performance. The objective of this initial research was to identify the most effective technique, which will serve as a foundation for the second phase of my research – the PhD. This subsequent phase will aim to enhance the identified technique’s efficiency by integrating additional data sources, such as social media, and employing methods like machine learning to develop an algorithm that automatically maps landslides based on their spectral signatures from satellite imagery. The ultimate goal is to assist stakeholders and first responders in identifying landslide locations and vulnerable landscapes, thereby improving relief efforts and disaster management strategies. Exciting, right? That’s why I’m dedicated to this project.
